readme example fix

README.md

@@ -40,7 +40,8 @@ Implementation of example based evaluation metrics for multi-label classificatio
 
 There is also multiset configuration available, which allows to calculate the metrics for multi-label classification with repeated labels.
 It uses the same definition as in previous case, but it works with multiset of labels. Thus, intersection, union, and cardinality for multisets are used instead.
-
+    
+    >>> multi_label_precision_recall_accuracy_fscore = evaluate.load("mdocekal/multi_label_precision_recall_accuracy_fscore", config_name="multiset")
     >>> results = multi_label_precision_recall_accuracy_fscore.compute(
                 predictions=[
                     [0, 1, 1]